Dynamic contrast enhanced MRI is performed to characterize tissue perfusion by observing and analyzing the passage of a bolus of contrast agent through the tissue. MR images are acquired at regular intervals during a time period that begins prior to the injection of the contrast agent, and extends through the contrast agent's passage through the tissue under study. To acquire the images, a pulse sequence is selected that produces images whose signal intensity is proportional to the concentration of contrast agent in the tissue, such as a perfusion-weighted echo-planar imaging (EPI) sequence. The MRI signal intensity of the tissue during this time period may be plotted versus time, to produce a time-course for the tissue. Time-courses may be constructed for single pixels, or for groups of neighboring pixels by combining the signal from multiple pixels. The signal intensity may be converted to a concentration of contrast agent with some simplifying assumptions regarding the tissue relaxivity.
For analytical purposes, the tissue vasculature may be modeled as a linear, time-invariant system (LTI). The output of a LTI system may be computed as the convolution of an input function with a transfer function. In this case, the input function is the contrast agent concentration in an artery feeding the tissue under study, referred to as the Arterial Input Function (AIF). The AIF is typically determined by selecting pixels corresponding to a feeding artery (or arteriole), extracting the time-course for the corresponding voxels, and converting the signal intensity to a concentration of contrast agent. An output function is computed in a similar manner from the time-course for the tissue voxels. A transfer function may be computed from an AIF and an output function. The transfer function describes the transformation of the input to the output, and reflects aspects of the tissue vasculature, such as regional blood flow, regional blood vessel density, and average regional vessel permeability, for example.
The transfer function is recovered by performing a deconvolution using the AIF and output concentration curves. Typically, a transfer function is calculated for every tissue voxel contributing to an image, on a voxel-by-voxel basis. From the transfer functions, maps of hemodynamic parameters may be computed and may be overlaid on an anatomical image for review. The maps of the hemodynamic parameters are known as parametric maps. A typical perfusion study in the brain may include maps of regional cerebral blood flow (rCBF), mean transit time (MTT), and regional Cerebral Blood Volume (rCBV), for example.
To obtain meaningful results for the parametric maps, it is important to choose an appropriate AIF, i.e., an AIF that corresponds to a feeding vessel for a tissue. For brain tumor perfusion studies, the AIF is typically chosen to correspond to a primary artery feeding the tumor. In the setting of a stroke study, the computation of parametric maps may require using different AIFs corresponding to the appropriate regional feeding vessels for different regions of the brain. Typically, a skilled reviewer, for example, a radiologist, examines an image to locate pixels corresponding to a blood vessel, and examines the time-course for those pixels. If the time-course exhibits the expected characteristics for a feeding vessel, it may be chosen as an AIF for the calculation of hemodynamic parameters in the surrounding tissue. The process of selecting AIFs may be time consuming and may require several iterations before the appropriate AIFs are identified. Methods for an automatic selection of an AIF are known in the prior art, however, these methods typically rely only on the mathematical characteristics of a time-course as a basis for selecting an appropriate AIF. Such automatic methods do not benefit from a reviewer's knowledge about the pertinent anatomy and physiology of the tissue under study. Accordingly, it would be advantageous to provide a user interface or tool that allows a reviewer or user, such as a radiologist, to interactively select an AIF and view parametric maps based on the selected AIF in real time.